SNSF-funded Scientist in Chemometrics or Computational Biology / SNSF-funded Scientistess in Chemometrics or Computational Biology

Dysregulation of Lipid Metabolism

Dysregulation of lipid metabolism plays a key role in the development and progression of metabolic disorders, including obesity, type 2 diabetes, and metabolic dysfunction-associated steatotic liver disease (MASLD). We are seeking a highly motivated scientist with a strong background in chemistry and expertise in mass spectrometry data analysis, chemometrics, and machine learning to join our team as part of the Precision-MASH project, which is fully funded by the Swiss National Science Foundation (SNSF).

What You Can Expect

The primary goal of this role is to advance the identification and screening of novel small molecules, with a particular focus on elucidating the structure and function of emerging lipids in metabolic disorders. The successful candidate will be responsible for developing computational pipelines for analyzing mass spectrometry datasets, integrating spectral data, building spectral libraries, and applying chemometric and machine learning methods to enable in-silico annotation.

Key Responsibilities

• Develop and apply computational pipelines for the identification and annotation of novel lipids.
• Perform in silico structural prediction of novel or low-abundance lipid species using advanced cheminformatics tools.
• Integrate multi-omics data with metabolic modeling approaches to investigate lipid flux and alterations in metabolic pathways.
• Design and implement chemometric and machine learning models for patient stratification based on spectral and imaging data.

Your Profile

The ideal candidate should possess a PhD or Master's degree with at least 5 years of research experience in computational biology, systems biology, bioinformatics, or chemometrics. Proficiency in at least one programming language (R, MATLAB, Python) is essential. A prior track record in mass spectrometry spectral analysis or mass spectrometry imaging analysis, in silico chemical annotation, and machine learning approaches is required. Knowledge of metabolism is a plus. We are looking for an enthusiastic individual who can work both independently and collaboratively within the team. Effective communication skills and fluency in both spoken and written English are essential.

What We Offer

We provide candidates with a supportive and state-of-the-art research environment that fosters scientific and professional development. The successful candidate will have the opportunity to work on a multidisciplinary research project, gaining training and experience with large datasets generated from both pre-clinical and clinical studies. The position is available from September 2025 or upon agreement.

Apply

Apply online using the form below. Only applications matching the job profile will be considered.

Questions about the Job?

For further information, please contact:

Prof. Mojgan Masoodi
Email: Show e-mail